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Comprehensive prognostic signatures in thyroid cancer: A summarized review for molecular signatures construction strategies

Xiaoyan Lu1,2† ,  Yuanyuan Zhang1,2† ,  Pei Yang1,2 ,  Minjun Yi1,2 ,  Luyao Wang1,2 ,  Jing Chen1,2 ,  Han Wang1,2 ,  Mengke Li1,2 ,  Yufei Jiang1,2 ,  Bingbing Guo1,2 ,  Wenyuan Lu1,2 ,  Shijia Li1,2 ,  Jiahao Chen1,2 ,  Yingying Lian1,2 ,  Xinyu Li1,2 ,  Binbin Zhao1,2 ,  Xiaoqing Wang1,2* ,  Yang An1,2*
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1 Department of Biochemistry and Molecular Biology, Cell Signal Transduction Laboratory, School of Basic Medicine, Bioinformatics Center, Henan University, Kaifeng, 475004, China
2 Henan Provincial Engineering Center for Tumor Molecular Medicine, Kaifeng Key laboratory of cell signal transduction, Kaifeng, 475004, China
GPD 2023, 2(3), 1138 https://doi.org/10.36922/gpd.1138
Submitted: 26 June 2023 | Accepted: 16 August 2023 | Published: 20 September 2023
© 2023 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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Abstract

Thyroid carcinoma (TC) is one of the most common endocrine carcinomas with an increasing rate of morbidity in recent decades. With a high risk of relapse and metastasis occurring in TC patients, it is essential to identify potential prognostic signatures for TC patients. Here, through a comprehensive review, we summarized 45 prognostic signatures for TC patients and concluded three main strategies for signature establishment after an extensive investigation. In particular, these signatures were classified according to different construction strategies, and the verification methods were summarized. Besides, we found that 18 key genes were overrepresented in reported signatures. This review provides a comprehensive understanding, systematic summary, and integrated analysis of current prognostic signatures of TC, which may help researchers to further understand cancer progression, construct prognostic signatures of TC, and guide future clinical treatment.

Keywords
Thyroid cancer
Prognostic signatures
Survival outcome
Funding
Program for Science and Technology Development in Henan Province
Innovation Project for College Students of Henan University
Natural Science Foundation of Henan Province
Program for Science and Technology Development in Kaifeng City
Conflict of interest
The authors declare they have no competing interests.
References
  1. Antonelli A, La Motta C, 2017, Novel therapeutic clues in thyroid carcinomas: The role of targeting cancer stem cells. Med Res Rev, 37(6): 1299–1317. https://doi.org/10.1002/med.21448

 

  1. Tofe S, Arguelles I, Forteza A, et al., 2023, Age-standardized incidence, mortality rate, and trend changes of thyroid cancer in the Balearic Islands during the 2000–2020 period: A population-based study. Eur Thyroid J, 12(3): e220183. https://doi.org/10.1530/ETJ-22-0183

 

  1. Gonzalez-Clavijo AM, Cuellar AA, Triana-Urrego J, et al., 2023, Metastatic differentiated thyroid cancer: Worst prognosis in patients with metachronous metastases. Endocrine, 81(1): 90–97. https://doi.org/10.1007/s12020-023-03302-0

 

  1. La Vecchia C, Malvezzi M, Bosetti C, et al., 2015, Thyroid cancer mortality and incidence: A global overview. Int J Cancer, 36(9): 2187–2195. https://doi.org/10.1002/ijc.29251

 

  1. Araque KA, Gubbi S, Klubo-Gwiezdzinska J, 2020, Updates on the management of thyroid cancer. Horm Metab Res, 52(8): 562–577. https://doi.org/10.1055/a-1089-7870

 

  1. Chmielik E, Rusinek D, Oczko-Wojciechowska M, et al., 2018, Heterogeneity of thyroid cancer. Pathobiology, 85(1–2): 117–129. https://doi.org/10.1159/000486422

 

  1. Lupoli GA, Fonderico F, Colarusso S, et al., 2005, Current management of differentiated thyroid carcinoma. Med Sci Monit, 11(12): RA368–RA373.

 

  1. Baloch ZW, Asa SL, Barletta JA, et al., 2022, Overview of the 2022 WHO classification of thyroid neoplasms. Endocr Pathol, 33(1): 27–63. https://doi.org/10.1007/s12022-022-09707-3

 

  1. Cabanillas ME, McFadden DG, Durante C, 2016, Thyroid cancer. Lancet, 388(10061): 2783–2795. https://doi.org/10.1016/S0140-6736(16)30172-6

 

  1. Metovic J, Cabutti F, Osella-Abate S, et al., 2023, Clinical and pathological features and gene expression profiles of clinically aggressive papillary thyroid carcinomas. Endocr Pathol. https://doi.org/10.1007/s12022-023-09769-x

 

  1. Liu Z, Zhao Q, Zeng W, et al., 2018, Prognosis of a rare subtype of thyroid cancer: Spindle cell thyroid carcinoma. Medicine (Baltimore), 97(45): e13053. https://doi.org/10.1097/MD.0000000000013053

 

  1. Soares P, Celestino R, Melo M, et al., 2014, Prognostic biomarkers in thyroid cancer. Virchows Arch, 464(3): 333–346. https://doi.org/10.1007/s00428-013-1521-2

 

  1. Yapa S, Mulla O, Green V, et al., 2017, The role of chemokines in thyroid carcinoma. Thyroid, 27(11): 1347–1359. https://doi.org/10.1089/thy.2016.0660

 

  1. Wolff L, Steindl A, Popov P, et al., 2023, Clinical characteristics, treatment, and long-term outcome of patients with brain metastases from thyroid cancer. Clin Exp Metastasis, 40(3): 217–226. https://doi.org/10.1007/s10585-023-10208-8

 

  1. Kang YJ, Stybayeva G, Hwang SH, 2023, Surgical completeness and safety of minimally invasive thyroidectomy in patients with thyroid cancer: A network meta-analysis. Surgery, 173(6): 1381–1390. https://doi.org/10.1016/j.surg.2023.02.021

 

  1. Sherman SI, 2003, Thyroid carcinoma. Lancet, 361(9356): 501–511. https://doi.org/10.1016/s0140-6736(03)12488-9

 

  1. Gulfidan G, Soylu M, Demirel D, et al., 2022, Systems biomarkers for papillary thyroid cancer prognosis and treatment through multi-omics networks. Arch Biochem Biophys, 715: 109085. https://doi.org/10.1016/j.abb.2021.109085

 

  1. Patel J, Klopper J, Cottrill EE, 2023, Molecular diagnostics in the evaluation of thyroid nodules: Current use and prospective opportunities. Front Endocrinol (Lausanne), 14: 1101410. https://doi.org/10.3389/fendo.2023.1101410

 

  1. Wu M, Yuan H, Li X, et al., 2019, Identification of a five-gene signature and establishment of a prognostic nomogram to predict progression-free interval of papillary thyroid carcinoma. Front Endocrinol (Lausanne), 10: 790. https://doi.org/10.3389/fendo.2019.00790

 

  1. Ruiz EM, Niu T, Zerfaoui M, et al., 2020, A novel gene panel for prediction of lymph-node metastasis and recurrence in patients with thyroid cancer. Surgery, 167(1): 73–79. https://doi.org/10.1016/j.surg.2019.06.058

 

  1. Teng H, Mao F, Liang J, et al., 2018, Transcriptomic signature associated with carcinogenesis and aggressiveness of papillary thyroid carcinoma. Theranostics, 8(16): 4345–4358. https://doi.org/10.7150/thno.26862

 

  1. Hu G, Feng HF, Zhan H, 2020, Identification of an autophagy-related signature predicting overall survival for papillary thyroid carcinoma. Dose Response, 18(1). https://doi.org/10.1177/1559325819899265

 

  1. Lin P, He Y, Wen DY, et al., 2018, Comprehensive analysis of the clinical significance and prospective molecular mechanisms of differentially expressed autophagy-related genes in thyroid cancer. Int J Oncol, 53(2): 603–619. https://doi.org/10.3892/ijo.2018.4404

 

  1. Lin P, Guo YN, Shi L, et al., 2019, Development of a prognostic index based on an immunogenomic landscape analysis of papillary thyroid cancer. Aging (Albany NY), 11(2): 480–500. https://doi.org/10.18632/aging.101754

 

  1. Qin R, Li C, Wang X, et al., 2021, Identification and validation of an immune-related prognostic signature and key gene in papillary thyroid carcinoma. Cancer Cell Int, 21(1): 378. https://doi.org/10.1186/s12935-021-02066-9

 

  1. Xue Y, Li J, Lu X, 2020, A novel immune-related prognostic signature for thyroid carcinoma. Technol Cancer Res Treat, 19. https://doi.org/10.1177/1533033820935860

 

  1. Ge M, Niu J, Hu P, et al., 2021, A ferroptosis-related signature robustly predicts clinical outcomes and associates with immune microenvironment for thyroid cancer. Front Med (Lausanne), 8: 637743. https://doi.org/10.3389/fmed.2021.637743

 

  1. Li Q, Wang P, Sun C, et al., 2019, Integrative analysis of methylation and transcriptome identified epigenetically regulated lncRNAs with prognostic relevance for thyroid cancer. Front Bioeng Biotechnol, 7: 439. https://doi.org/10.3389/fbioe.2019.00439

 

  1. Liu T, You X, Sui J, et al., 2019, Prognostic value of a two-microRNA signature for papillary thyroid cancer and a bioinformatic analysis of their possible functions. J Cell Biochem, 120: 7185–7198. https://doi.org/10.1002/jcb.27993

 

  1. Ma Y, Yin S, Liu XF, et al., 2021, Comprehensive analysis of the functions and prognostic value of RNA-binding proteins in thyroid cancer. Front Oncol, 11: 625007. https://doi.org/10.3389/fonc.2021.625007

 

  1. Qian X, Tang J, Li L, et al., 2021, A new ferroptosis-related gene model for prognostic prediction of papillary thyroid carcinoma. Bioengineered, 12(1): 2341–2351. https://doi.org/10.1080/21655979.2021.1935400

 

  1. Xu F, Xu H, Li Z, et al., 2021, Glycolysis-based genes are potential biomarkers in thyroid cancer. Front Oncol, 11: 534838. https://doi.org/10.3389/fonc.2021.534838

 

  1. You X, Yang S, Sui J, et al., 2018, Molecular characterization of papillary thyroid carcinoma: A potential three-lncRNA prognostic signature. Cancer Manag Res, 10: 4297–4310. https://doi.org/10.2147/CMAR.S174874

 

  1. Huang Y, Yi T, Liu Y, et al., 2021, The landscape of tumors-infiltrate immune cells in papillary thyroid carcinoma and its prognostic value. PeerJ, 9: e11494. https://doi.org/10.7717/peerj.11494

 

  1. Ren H, Liu X, Li F, et al., 2021, Identification of a six gene prognosis signature for papillary thyroid cancer using multi-omics methods and bioinformatics analysis. Front Oncol, 11: 624421. https://doi.org/10.3389/fonc.2021.624421

 

  1. Ruchong P, Haiping T, Xiang W, 2021, A five-gene prognostic nomogram predicting disease-free survival of differentiated thyroid cancer. Dis Markers, 2021: 5510780. https://doi.org/10.1155/2021/5510780

 

  1. Saftencu M, Braicu C, Cojocneanu R, et al., 2019, Gene expression patterns unveil new insights in papillary thyroid cancer. Medicina (Kaunas), 55(8): 500. https://doi.org/10.3390/medicina55080500

 

  1. Wu M, Li S, Han J, et al., 2020, Progression risk assessment of post-surgical papillary thyroid carcinoma based on circular RNA-associated competing endogenous RNA mechanisms. Front Cell Dev Biol, 8: 606327. https://doi.org/10.3389/fcell.2020.606327

 

  1. Xu L, Liu F, Li H, et al., 2021, Comprehensive characterization of pathological stage-related genes of papillary thyroid cancer along with survival prediction. J Cell Mol Med, 25(17): 8390–8404. https://doi.org/10.1111/jcmm.16799

 

  1. Zhong LK, Gan XX, Deng XY, et al., 2020, Potential five-mRNA signature model for the prediction of prognosis in patients with papillary thyroid carcinoma. Oncol Lett, 20(3): 2302–2310. https://doi.org/10.3892/ol.2020.11781

 

  1. Li Q, Li H, Zhang L, et al., 2017, Identification of novel long non-coding RNA biomarkers for prognosis prediction of papillary thyroid cancer. Oncotarget, 8(28): 46136–46144. https://doi.org/10.18632/oncotarget.17556

 

  1. Luo YH, Liang L, He RQ, et al., 2017, RNA-sequencing investigation identifies an effective risk score generated by three novel lncRNAs for the survival of papillary thyroid cancer patients. Oncotarget, 8(43): 74139–74158. https://doi.org/10.18632/oncotarget.18274

 

  1. Zhang Y, Jin T, Shen H, et al., 2019, Identification of long non-coding RNA expression profiles and co-expression genes in thyroid carcinoma based on the cancer genome atlas (TCGA) database. Med Sci Monit, 25: 9752–9769. https://doi.org/10.12659/MSM.917845

 

  1. Chengfeng X, Gengming C, Junjia Z, et al., 2019, MicroRNA signature predicts survival in papillary thyroid carcinoma. J Cell Biochem, 120(10): 17050–17058. https://doi.org/10.1002/jcb.28966

 

  1. Li Q, Jiang S, Feng T, et al., 2021, Identification of the EMT-related genes signature for predicting occurrence and progression in thyroid cancer. Onco Targets Ther, 14: 3119–3131. https://doi.org/10.2147/OTT.S301127

 

  1. Lin R, Fogarty CE, Ma B, et al., 2021, Identification of ferroptosis genes in immune infiltration and prognosis in thyroid papillary carcinoma using network analysis. BMC Genomics, 22(1): 576. https://doi.org/10.1186/s12864-021-07895-6

 

  1. Lv L, Cao L, Hu G, et al., 2020, Methylation-driven genes identified as novel prognostic indicators for thyroid carcinoma. Front Genet, 11: 294. https://doi.org/10.3389/fgene.2020.00294

 

  1. Xu N, Chen J, He G, et al., 2020, Prognostic values of m6A RNA methylation regulators in differentiated thyroid carcinoma. J Cancer, 11(17): 5187–5197. https://doi.org/10.7150/jca.41193

 

  1. Hou J, Shan H, Zhang Y, et al., 2020, m6A RNA methylation regulators have prognostic value in papillary thyroid carcinoma. Am J Otolaryngol, 41(4): 102547. https://doi.org/10.1016/j.amjoto.2020.102547

 

  1. Suh HY, Choi H, Paeng JC, et al., 2019, Comprehensive gene expression analysis for exploring the association between glucose metabolism and differentiation of thyroid cancer. BMC Cancer, 19(1): 1260. https://doi.org/10.1186/s12885-019-6482-7

 

  1. Han B, Yang M, Yang X, et al., 2021, Systematic analysis of survival-associated alternative splicing signatures in thyroid carcinoma. Front Oncol, 11: 561457. https://doi.org/10.3389/fonc.2021.561457

 

  1. Lin P, He RQ, Huang ZG, et al., 2019, Role of global aberrant alternative splicing events in papillary thyroid cancer prognosis. Aging (Albany NY), 11(7): 2082–2097. https://doi.org/10.18632/aging.101902

 

  1. Han Y, Yu X, Yin Y, et al., 2021, Identification of potential BRAF inhibitor joint therapy targets in PTC based on WGCAN and DCGA. J Cancer, 12(6): 1779–1791. https://doi.org/10.7150/jca.51551

 

  1. Gandolfi G, Ragazzi M, de Biase D, et al., 2018, Genome-wide profiling identifies the THYT1 signature as a distinctive feature of widely metastatic Papillary Thyroid Carcinomas. Oncotarget, 9(2): 1813–1825. https://doi.org/10.18632/oncotarget.22805

 

  1. Zhang Y, Zhang R, Liang F, 2020, Identification of metabolism-associated prostate cancer subtypes and construction of a prognostic risk model. Front Oncol, 10: 598801. https://doi.org/10.3389/fonc.2020.598801

 

  1. Wang K, Xu J, Zhao L, et al., 2020, Prognostic lncRNA, miRNA, and mRNA signatures in papillary thyroid carcinoma. Front Genet, 11: 805. https://doi.org/10.3389/fgene.2020.00805

 

  1. Yu H, Guo P, Xie X, et al., 2017, Ferroptosis, a new form of cell death, and its relationships with tumourous diseases. J Cell Mol Med, 21(4): 648–657. https://doi.org/10.1111/jcmm.13008

 

  1. Murakami H, Hayashi M, Terada S, et al., 2023, Medroxyprogesterone acetate-resistant endometrial cancer cells are susceptible to ferroptosis inducers. Life Sci, 325: 121753. https://doi.org/10.1016/j.lfs.2023.121753

 

  1. Cao JY, Dixon SJ, 2016, Mechanisms of ferroptosis. Cell Mol Life Sci, 73(11–12): 2195–2209. https://doi.org/10.1007/s00018-016-2194-1

 

  1. Kim SE, Zhang L, Ma K, et al., 2016, Ultrasmall nanoparticles induce ferroptosis in nutrient-deprived cancer cells and suppress tumour growth. Nat Nanotechnol, 11(11): 977–985. https://doi.org/10.1038/nnano.2016.164

 

  1. Dongre A, Weinberg RA, 2019, New insights into the mechanisms of epithelial-mesenchymal transition and implications for cancer. Nat Rev Mol Cell Biol, 20(2): 69–84. https://doi.org/10.1038/s41580-018-0080-4

 

  1. Dawson MA, Kouzarides T, 2012, Cancer epigenetics: From mechanism to therapy. Cell, 150(1): 12–27. https://doi.org/10.1016/j.cell.2012.06.013

 

  1. Ilango S, Paital B, Jayachandran P, et al., 2020, Epigenetic alterations in cancer. Front Biosci, (Landmark Ed), 25(6): 1058–1109. https://doi.org/10.2741/4847

 

  1. Zafon C, Gil J, Perez-Gonzalez B, et al., 2019, DNA methylation in thyroid cancer. Endocr Relat Cancer, 26(7): R415–R439. https://doi.org/10.1530/ERC-19-0093

 

  1. Russo D, Damante G, Puxeddu E, et al., 2011, Epigenetics of thyroid cancer and novel therapeutic targets. J Mol Endocrinol, 46(3): R73–R81. https://doi.org/10.1530/JME-10-0150

 

  1. Wang X, Fu X, Zhang J, et al., 2020, Identification and validation of m6A RNA methylation regulators with clinical prognostic value in Papillary thyroid cancer. Cancer Cell Int, 20: 203. https://doi.org/10.1186/s12935-020-01283-y

 

  1. Kushchayeva Y, Kushchayev S, Jensen K, et al., 2022, Impaired glucose metabolism, anti-diabetes medications, and risk of thyroid cancer. Cancers (Basel), 14(3): 555. https://doi.org/10.3390/cancers14030555

 

  1. Heydarzadeh S, Moshtaghie AA, Daneshpoor M, et al., 2020, Regulators of glucose uptake in thyroid cancer cell lines. Cell Commun Signal, 18(1): 83. https://doi.org/10.1186/s12964-020-00586-x

 

  1. Davidson CD, Tomczak JA, Amiel E, et al., 2022, Inhibition of glycogen metabolism induces reactive oxygen species-dependent cytotoxicity in anaplastic thyroid cancer in female mice. Endocrinology, 163(12): bqac169. https://doi.org/10.1210/endocr/bqac169

 

  1. Matsuzu K, Segade F, Matsuzu U, et al., 2004, Differential expression of glucose transporters in normal and pathologic thyroid tissue. Thyroid, 14(10): 806–812. https://doi.org/10.1089/thy.2004.14.806

 

  1. Marima R, Francies FZ, Hull R, et al., 2021, MicroRNA and alternative mRNA splicing events in cancer drug response/ resistance: Potent therapeutic targets. Biomedicines, 9(12): 1818. https://doi.org/10.3390/biomedicines9121818

 

  1. Climente-Gonzalez H, Porta-Pardo E, Godzik A, et al., 2017, The functional impact of alternative splicing in cancer. Cell Rep, 20(9): 2215–2226. https://doi.org/10.1016/j.celrep.2017.08.012

 

  1. Park J, Kim D, Lee JO, et al., 2022, Dissection of molecular and histological subtypes of papillary thyroid cancer using alternative splicing profiles. Exp Mol Med, 54(3): 263–272. https://doi.org/10.1038/s12276-022-00740-0

 

  1. Oltean S, Bates DO, 2014, Hallmarks of alternative splicing in cancer. Oncogene, 33(46): 5311–5318. https://doi.org/10.1038/onc.2013.533

 

  1. Abdullah MI, Junit SM, Ng KL, et al., 2019, Papillary thyroid cancer: Genetic alterations and molecular biomarker investigations. Int J Med Sci, 16(3): 450–460. https://doi.org/10.7150/ijms.29935

 

  1. Nikiforov YE, Nikiforova MN, 2011, Molecular genetics and diagnosis of thyroid cancer. Nat Rev Endocrinol, 7(10): 569–580. https://doi.org/10.1038/nrendo.2011.142

 

  1. Zantut-Wittmann DE, Laus AC, Moreno DA, et al., 2023, Extremely aggressive course in a poorly differentiated thyroid carcinoma presenting a double mutation of the TERT promoter. Am J Med Sci, 365(6): 532–537. https://doi.org/10.1016/j.amjms.2023.03.019

 

  1. Chen H, Ma X, Yang M, 2020, A methylomics-associated nomogram predicts recurrence-free survival of thyroid papillary carcinoma. Cancer Med, 9(19): 7183–7193. https://doi.org/10.1002/cam4.3388

 

  1. Chen Z, Liu X, Liu F, et al., 2021, Identification of 4-methylation driven genes based prognostic signature in thyroid cancer: An integrative analysis based on the methylmix algorithm. Aging (Albany NY), 13(16): 20164– 20178. https://doi.org/10.18632/aging.203338

 

  1. Mou Y, Wang J, Wu J, et al., 2019, Ferroptosis, a new form of cell death: Opportunities and challenges in cancer. J Hematol Oncol, 12(1): 34. https://doi.org/10.1186/s13045-019-0720-y

 

  1. Zhao H, De Souza C, Kumar VE, et al., 2021, Long non-coding RNA signatures as predictors of prognosis in thyroid cancer: A narrative review. Ann Transl Med, 9(4): 359. https://doi.org/10.21037/atm-20-8191
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